%0 Conference Proceedings %T SIGMORPHON–UniMorph 2022 Shared Task 0: Generalization and Typologically Diverse Morphological Inflection %A Kodner, Jordan %A Khalifa, Salam %A Batsuren, Khuyagbaatar %A Dolatian, Hossep %A Cotterell, Ryan %A Akkus, Faruk %A Anastasopoulos, Antonios %A Andrushko, Taras %A Arora, Aryaman %A Atanalov, Nona %A Bella, Gábor %A Budianskaya, Elena %A Ghanggo Ate, Yustinus %A Goldman, Omer %A Guriel, David %A Guriel, Simon %A Guriel-Agiashvili, Silvia %A Kieraś, Witold %A Krizhanovsky, Andrew %A Krizhanovsky, Natalia %A Marchenko, Igor %A Markowska, Magdalena %A Mashkovtseva, Polina %A Nepomniashchaya, Maria %A Rodionova, Daria %A Scheifer, Karina %A Sorova, Alexandra %A Yemelina, Anastasia %A Young, Jeremiah %A Vylomova, Ekaterina %Y Nicolai, Garrett %Y Chodroff, Eleanor %S Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology %D 2022 %8 July %I Association for Computational Linguistics %C Seattle, Washington %F kodner-etal-2022-sigmorphon %X The 2022 SIGMORPHON–UniMorph shared task on large scale morphological inflection generation included a wide range of typologically diverse languages: 33 languages from 11 top-level language families: Arabic (Modern Standard), Assamese, Braj, Chukchi, Eastern Armenian, Evenki, Georgian, Gothic, Gujarati, Hebrew, Hungarian, Itelmen, Karelian, Kazakh, Ket, Khalkha Mongolian, Kholosi, Korean, Lamahalot, Low German, Ludic, Magahi, Middle Low German, Old English, Old High German, Old Norse, Polish, Pomak, Slovak, Turkish, Upper Sorbian, Veps, and Xibe. We emphasize generalization along different dimensions this year by evaluating test items with unseen lemmas and unseen features separately under small and large training conditions. Across the five submitted systems and two baselines, the prediction of inflections with unseen features proved challenging, with average performance decreased substantially from last year. This was true even for languages for which the forms were in principle predictable, which suggests that further work is needed in designing systems that capture the various types of generalization required for the world’s languages. %R 10.18653/v1/2022.sigmorphon-1.19 %U https://aclanthology.org/2022.sigmorphon-1.19 %U https://doi.org/10.18653/v1/2022.sigmorphon-1.19 %P 176-203